Uncertainty in sea level rise projections due to the dependence between contributors
Sea level rises at an accelerating pace threatening coastal communities all over the world. In this context sea level projections are key tools to help risk mitigation and adaptation. Sea level projections are often made using models of the main contributors to sea level rise (e.g. thermal expansion...
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Format: | Report |
Language: | unknown |
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EarthArXiv
2018
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Online Access: | https://dx.doi.org/10.17605/osf.io/uvw3s https://eartharxiv.org/uvw3s/ |
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author | Le Bars, Dewi |
author_facet | Le Bars, Dewi |
author_sort | Le Bars, Dewi |
collection | DataCite |
description | Sea level rises at an accelerating pace threatening coastal communities all over the world. In this context sea level projections are key tools to help risk mitigation and adaptation. Sea level projections are often made using models of the main contributors to sea level rise (e.g. thermal expansion, glaciers, ice sheets...). To obtain the total sea level these contributions are added, therefore the uncertainty of total sea level depends on the correlation between the uncertainties of the contributors. This fact is important to understand the differences in the uncertainty of sea level projections from different methods. Using two process-based models to project sea level for the 21st century, we show how to model the correlation structure and its time dependence. In these models the correlation primarily arises from uncertainty of future global mean surface temperature that correlates with almost all contributors. Assuming that sea level contributors are independent of each other, an assumption made in many sea level projections, underestimates the uncertainty in sea level projections. As a result, high-end low probability events that are important for decision making are underestimated. The uncertainty in the strength of the dependence between contributors is also explored. New dependence relation between the uncertainty of dynamical processes, and surface mass balance in glaciers and ice sheets are introduced in our model. Total sea level uncertainty is found to be as sensitive to the dependence between contributors as to uncertainty in individual contributors like thermal expansion and Greenland ice sheet. |
format | Report |
genre | Greenland Ice Sheet |
genre_facet | Greenland Ice Sheet |
geographic | Greenland |
geographic_facet | Greenland |
id | ftdatacite:10.17605/osf.io/uvw3s |
institution | Open Polar |
language | unknown |
op_collection_id | ftdatacite |
op_doi | https://doi.org/10.17605/osf.io/uvw3s |
op_rights | CC-By Attribution 4.0 International |
publishDate | 2018 |
publisher | EarthArXiv |
record_format | openpolar |
spelling | ftdatacite:10.17605/osf.io/uvw3s 2025-01-16T22:13:18+00:00 Uncertainty in sea level rise projections due to the dependence between contributors Le Bars, Dewi 2018 https://dx.doi.org/10.17605/osf.io/uvw3s https://eartharxiv.org/uvw3s/ unknown EarthArXiv CC-By Attribution 4.0 International Physical Sciences and Mathematics Statistics and Probability Statistical Models Probability Applied Statistics Oceanography and Atmospheric Sciences and Meteorology Climate Environmental Sciences Earth Sciences Preprint Text article-journal ScholarlyArticle 2018 ftdatacite https://doi.org/10.17605/osf.io/uvw3s 2021-11-05T12:55:41Z Sea level rises at an accelerating pace threatening coastal communities all over the world. In this context sea level projections are key tools to help risk mitigation and adaptation. Sea level projections are often made using models of the main contributors to sea level rise (e.g. thermal expansion, glaciers, ice sheets...). To obtain the total sea level these contributions are added, therefore the uncertainty of total sea level depends on the correlation between the uncertainties of the contributors. This fact is important to understand the differences in the uncertainty of sea level projections from different methods. Using two process-based models to project sea level for the 21st century, we show how to model the correlation structure and its time dependence. In these models the correlation primarily arises from uncertainty of future global mean surface temperature that correlates with almost all contributors. Assuming that sea level contributors are independent of each other, an assumption made in many sea level projections, underestimates the uncertainty in sea level projections. As a result, high-end low probability events that are important for decision making are underestimated. The uncertainty in the strength of the dependence between contributors is also explored. New dependence relation between the uncertainty of dynamical processes, and surface mass balance in glaciers and ice sheets are introduced in our model. Total sea level uncertainty is found to be as sensitive to the dependence between contributors as to uncertainty in individual contributors like thermal expansion and Greenland ice sheet. Report Greenland Ice Sheet DataCite Greenland |
spellingShingle | Physical Sciences and Mathematics Statistics and Probability Statistical Models Probability Applied Statistics Oceanography and Atmospheric Sciences and Meteorology Climate Environmental Sciences Earth Sciences Le Bars, Dewi Uncertainty in sea level rise projections due to the dependence between contributors |
title | Uncertainty in sea level rise projections due to the dependence between contributors |
title_full | Uncertainty in sea level rise projections due to the dependence between contributors |
title_fullStr | Uncertainty in sea level rise projections due to the dependence between contributors |
title_full_unstemmed | Uncertainty in sea level rise projections due to the dependence between contributors |
title_short | Uncertainty in sea level rise projections due to the dependence between contributors |
title_sort | uncertainty in sea level rise projections due to the dependence between contributors |
topic | Physical Sciences and Mathematics Statistics and Probability Statistical Models Probability Applied Statistics Oceanography and Atmospheric Sciences and Meteorology Climate Environmental Sciences Earth Sciences |
topic_facet | Physical Sciences and Mathematics Statistics and Probability Statistical Models Probability Applied Statistics Oceanography and Atmospheric Sciences and Meteorology Climate Environmental Sciences Earth Sciences |
url | https://dx.doi.org/10.17605/osf.io/uvw3s https://eartharxiv.org/uvw3s/ |